Modeling and inference of genomic signatures of polygenic selection driving fast adaptation

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In fast adaptation, polygenic selection may be more important than selection on single genes. The goal of this project is to analyze a mathematical model of a quantitative trait that is subject to a combination of directional and stabilizing selection, mutation, and random genetic drift. In the first funding period, we have shown that for very large population sizes this model predicts two qualitatively different modes of fast polygenic adaptation: selective sweeps whereby large shifts in the allele frequencies occur at a few major loci and evolution via small changes in the allele frequencies at many minor loci. Here we study the influence of random genetic drift in finite populations (that may be subject to size changes). Furthermore, we develop methods to detect genomic signals of fast polygenic adaptation at mostly minor loci. Finally, we extend our original one-trait model by allowing polygenic selection on multiple traits (pleiotropy).